(1) Field of the Invention
The present invention relates to a noise suppression apparatus that suppresses noise components in a signal that is a received signal of radio wave communication and the like which is contaminated with noise, and in particular, to noise canceling technology for FM receiving apparatuses.
(2) Description of the Related Art
The spectrum subtraction method and the Wiener filter method are two of the most frequently quoted methods in conventional noise suppression technology. These methods are based on the principle of: using a time-series signal contaminated with noise as input; estimating a noise spectrum by assuming that a time segment without sound is a noise segment; and subtracting only the noise component from the inputted signal. With either method, a noise spectrum estimated in order to adjust the amount of noise suppression is generally multiplied by a coefficient α that is a multiplication constant.|Y(f)|=|X(f)|−α|N(f)|
In the equation above, X(f) represents an input signal spectrum, N(f) an estimated noise spectrum, Y(f) a signal spectrum after noise suppression, and |X(f)| an amplitude spectrum or a power spectrum of the input signal spectrum X(f). Similarly, |N(f)| and |Y(f)| respectively represent an amplitude spectrum or a power spectrum of N(f) and Y(f).
FIG. 1 is a block diagram showing a configuration example of a noise suppression apparatus using the spectrum subtraction method. To give a simple explanation, the noise suppression apparatus uses as input a time series signal (x(t)=y(t)+n(t)) contaminated with a noise n(t), converts the input signal x(t) at a frequency conversion unit 1001 into a spectrum signal X(f) while simultaneously inputting the input signal x(t) into a sound/noise judging unit 1002, and extracts a noise portion from the input signal x(t) at the sound/noise judging unit 1002. A noise estimation unit 1003 learns the spectrum signal of the noise portion extracted at the sound/noise judging unit 1002 to generate an estimated noise spectrum N(f), whereby the estimated noise spectrum N(f) is subtracted from the input signal spectrum X(f) at a noise suppression unit 1004. After subtraction, the time series signal y(t) is restored from the spectrum signal Y(f) at an inverse frequency conversion unit 1005.
Furthermore, a method is proposed for suppressing generation of abnormal processing noise or reduction in recognition rate due to estimation errors in the estimated noise spectrum, by performing clipping that prevents the value of the signal spectrum after noise suppression from dropping below a predetermined value or by performing smoothing using moving averages and the like on the signal spectrum after noise suppression in order to reduce distortion of the voice spectrum (refer to Japanese Unexamined Patent Application Publication No. 2002-221988).
FIG. 2 is a block diagram showing a configuration example of a noise suppression apparatus that performs clipping during noise suppression using the spectrum subtraction method. When performing subtraction at the noise suppression unit 1004′, clipping is performed such that the noise spectrum subtraction result does not drop to or fall below a predetermined value, and a smoothed spectrum signal Z(f) is obtained by a moving average process and the like at a spectrum correction unit 1006. In the following equation, α represents a coefficient while Th represents a threshold.|Y′(f)|=max(|X(f)|−α|N(f)|,Th)
On the other hand, when contemplating a case where a target signal on which noise suppression is to be performed is a received signal of FM radio broadcast, noise characteristics change in accordance with constantly changing electric field strengths. Furthermore, to begin with, it is extremely difficult to extract a noise portion from a signal that contains hardly any soundless portions such as FM radio broadcast and estimate a noise spectrum. Meanwhile, when focusing on heat noise generated at a receiver or, more particularly, at an RF element as a noise generating factor, since elements that become noise generating factors differ according to the strength of the receiving electric field, it is possible to calculate and pattern in advance a noise spectrum for each electric field strength. FIG. 3 is a block diagram showing a configuration of a noise suppression apparatus that stores a noise spectrum pattern for each electric field strength and suppresses noise using the spectrum subtraction method. In this example, significant noise suppression effects are produced by patterning a noise spectrum per electric field strength (refer to Japanese Patent No. 2760240). In this example, estimation of a noise spectrum is performed by using as input an electric field signal S(t) representing an electric field strength together with an input signal instead of providing the sound/noise judging unit 1002 shown in FIG. 1, and reading out pattern data stored in a pattern table 1007 based on the electric field signal S(t) at the noise estimation unit 1003.
However, as shown in Japanese Patent No. 2760240, when storing a noise spectrum calculated in advance as pattern data and using the noise spectrum in an estimated noise spectrum, since actually occurring noise characteristics vary according to individual differences among RFs, there is a problem in that variations in noise suppression capabilities occur among sets such that, for example, a desired noise suppression effect is not obtained due to differences occurring between a noise spectrum pattern read out from the pattern table 1007 and an actually occurring noise spectrum. FIG. 4A is a diagram showing variations in input/output characteristics per RF. FIG. 4B is a diagram showing variations in noise spectrums in the same electric field. FIG. 5 is a diagram showing a deviation between a noise spectrum pattern stored in the pattern table 1007 and noise spectrums actually occurring per RF samples using as an example a case where the electric field strength is 10 [dBuV]. In FIG. 5, while the noise spectrum of sample B (dashed line) approximately matches the noise spectrum pattern (bold line) in the pattern table 1007, the noise spectrum of sample A (solid line) deviates significantly from the noise spectrum pattern. When performing noise suppression in this state, since subtraction is performed using a noise spectrum pattern that is at a lower level than the actual noise spectrum, the insufficient suppression amount leads to a decrease in suppressive capabilities. Conversely, when the noise spectrum pattern is at a higher level than the actual noise spectrum, excessive subtraction becomes a factor for generating of abnormal processing noise.
Dissolution of individual differences between RFs requires the use of high-quality components with little variation through the improvement of current RFs, and may result in significant increases in cost. In addition, there is a problem in that even when re-calculating noise spectrum in the adjustment stage and restructuring pattern data without enhancing the capabilities of RFs, a significantly large number of man-hours are required.